In many computer applications (e.g., computer vision or computer graphics), three-dimensional (or 3D) physical objects or surfaces thereof are typically described or represented using models such as 3D meshes, which are sometimes called textured meshes or polygon meshes, that represent both shapes and textures of such objects. A textured mesh of an object typically comprises two parts: a 3D representation of the object defined by vertices and/or edges of the object, and polygonal shapes or faces that extend between such vertices and edges and represent a texture of the object. From a purely digital perspective, a textured mesh thus defines both a volume and an appearance of the object in a manner that may be readily utilized in connection with one or more graphical applications.
Forming a 3D model of an object (e.g., a textured mesh) typically requires the use of imaging devices and computer-driven modeling techniques to capture digital imagery of the object and to generate a physical representation of the object. For example, the physical representation of the object may be defined by a set of points in 3D space, which may be obtained from a depth image of the object or other ranging data, or from one or more two-dimensional (or 2D) images of the object, such as by modeling the object using stereo or structure-from-motion (or SFM) algorithms. Using such data, a depth model, such as a point cloud, of the object may be defined for the object, including a set of points that may be described with respect to Cartesian coordinates. Subsequently, a textured mesh or other 3D model may be generated for the object using a visual digital image and the depth model, such as by mapping or patching portions or sectors of the visual digital image to the polygonal shapes defined by the respective points of the depth model.
Generating a depth model of an object from imaging data captured from the object (e.g., a plurality of depth images or other point samples of depths or ranges to an object) is a computationally expensive process, however, that tends to consume or occupy substantial amounts of available data storage, processing and transmission capacities, and may require comparatively lengthy processing times. Moreover, processes by which depth images or other point samples of depth are captured typically do not effectively sample an object's shape at its sharpest points, e.g., corners or edges of the object, regardless of their density. Thus, textured meshes that are generated based on depth images or other point samples typically do not represent corners or edges of objects with sufficient fidelity, and feature meshed surfaces having suboptimal clarity. Effects of such phenomena are exacerbated when an object from which a depth model is desired is in relative motion with respect to an imaging device with which the color image and the depth images are captured. Increasing densities of depth images or other point samples of an object have limited effect in enhancing the accuracy of depth models that are derived therefrom, while greatly increasing the extent of computer resources that are required in order to process such depth images or point samples, or to form a textured mesh therefrom.